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Data Scientist 4
3 years ago
Zynga is a leading developer of the world’s most popular social games that are played by people around the world every single day. To-date, more than 1 billion people have played our games across Web and mobile, including Words With Friends, FarmVille, Zynga Poker, Merge Dragons, Empires & Puzzles, Hit it Rich! Slots and CSR.
Zynga’s Programmatic Ads Platform team uses our outstanding and expansive data to acquire high value users for our gaming portfolio. We strive for a better understanding of our players which translates into challenges and features that delight them.
Here’s where you would come in: identify and formalize problems related to campaign and bidding optimization. Design and develop systems and machine learning models to optimize campaigns at scale and low-latency. Be innovative, be creative, use every bit of that key commodity – data. Millions of people play Zynga games every day, so our data is tremendously rich, and we have a lot of it!
We will rely on you to communicate your findings to your peers – both technical and non-technical. Your solutions to difficult problems will need to be demonstrably impactful, visual and maintainable. You will collaborate with engineering teams to build campaign bidders and optimizers. You will collaborate with User Acquisition Managers, Product Managers, and Engineers to deliver business impact.
Responsibilities:
- Design and implement scalable systems and models to experiment with campaigns and creatives across channels and acquire users at scale
- Work with large amounts of data to find and realize opportunities to acquire and re-target users profitably delivering unambiguous business metric impact
- Craft effective campaign strategies to acquire users across a multitude of user acquisition channels
- Drive and empower user acquisition team to make quantitatively informed, evidence-based decisions - through custom visualizations, and ETLs to augment user data
- Design, test, verify, and implement machine learning models with Zynga’s games that impact millions of users. Models may include but not limited to LTV modeling, campaign bid recommendations, budget allocation, clustering/segmentation, forecasting, fraud detection, and/or reinforcement learning
- Build services and applications that improve the effectiveness of campaigns, creatives, ad networks, and/or user segments.
Required Skills and Experience:
- B.S. or B.A. in Math, Statistics, Comp Sci, Engineering, or other quantitative field required; Masters, MBA or PhD preferred
- 5+ years of relevant work experience in data science or analytics role in a Machine Learning team
- Familiarity with OpenRTB, mobile programmatic ad tech, performance marketing, and/or user acquisition landscape is a big plus
- Proficient in Python/Java/C/C++/C#/Go; Demonstrated experience in designing distributed systems and working with low latency systems
- Strong experience in SQL;
- Ability to build and maintain software services and systems at scale; experience in deploying services in at least one cloud provider (AWS, Google Cloud or Azure)
- Proven experience with some of the following: machine learning, predictive modeling, deep learning
- Experience in analyzing large datasets, preferably in a Hadoop or Spark environment, and deploying production-ready systems at scale
- Strong written and oral communication skills
- Strong passion for gaming and performance marketing!
Zynga is an equal opportunity employer. We are proud of our broad community; we do not discriminate on the basis of race, sex, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, medical condition, disability, or any other class or characteristic protected by applicable law. We welcome job-seekers, players, employees, and partners from all backgrounds. Join us!
We will consider all qualified job-seekers with criminal histories in a manner consistent with applicable law.
Zynga is committed to providing reasonable accommodation to applicants with disabilities. If you need an accommodation during the interview process, please let us know.
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